Low coverage genomic data resolve the population divergence and gene flow history of an Australian rain forest fig wasp

AbstractPopulation divergence and gene flow are key processes in evolution and ecology. Model-based analysis of genome-wide datasets allows discrimination between alternative scenarios for these processes even in non-model taxa. We used two complementary approaches (one based on the blockwise site frequency spectrum (bSFS), the second on the Pairwise Sequentially Markovian Coalescent (PSMC)) to infer the divergence history of a fig wasp, Pleistodontes nigriventris. Pleistodontes nigriventris and its fig tree mutualist Ficus watkinsiana are restricted to rain forest patches along the eastern coast of Australia, and are separated into northern and southern populations by two dry forest corridors (the Burdekin and St. Lawrence Gaps). We generated whole genome sequence data for two haploid males per population and used the bSFS approach to infer the timing of divergence between northern and southern populations of P. nigriventris, and to discriminate between alternative isolation with migration (IM) and instantaneous admixture (ADM) models of post divergence gene flow. Pleistodontes nigriventris has low genetic diversity (π = 0.0008), to our knowledge one of the lowest estimates reported for a sexually reproducing arthropod. We find strongest support for an ADM model in which the two populations diverged ca. 196kya in the late Pleistocene, with almost 25% of northern lineages introduced from the south during an admixture event ca. 57kya. This divergence history is highly concordant with individual population demographies inferred from each pair of haploid males using PSMC. Our analysis illustrates the inferences possible with genome-level data for small population samples of tiny, non-model organisms and adds to a growing body of knowledge on the population structure of Australian rain forest taxa.

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Low‐coverage genomic data resolve the population divergence and gene flow history of an Australian rain forest fig wasp

Molecular Ecology ◽

10.1111/mec.15523 ◽

2020 ◽

Vol 29 (19) ◽

pp. 3649-3666

Author(s):

Lisa Cooper ◽

Lynsey Bunnefeld ◽

Jack Hearn ◽

James M. Cook ◽

Konrad Lohse ◽

...

Keyword(s):

Gene Flow ◽

Rain Forest ◽

Genomic Data ◽

Population Divergence ◽

Fig Wasp ◽

History Of ◽

Low Coverage

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Inversions shape the divergence of Drosophila pseudoobscura and D. persimilis on multiple timescales

10.1101/842047 ◽

2019 ◽

Cited By ~ 2

Author(s):

Katharine L Korunes ◽

Carlos A Machado ◽

Mohamed AF Noor

Keyword(s):

Gene Flow ◽

Evolutionary History ◽

Sequence Data ◽

Sequence Divergence ◽

Whole Genome Sequence ◽

Drosophila Pseudoobscura ◽

Ancestral Polymorphism ◽

Chromosomal Inversions ◽

History Of ◽

Ancient Gene

AbstractBy shaping meiotic recombination, chromosomal inversions can influence genetic exchange between hybridizing species. Despite the recognized importance of inversions in evolutionary processes such as divergence and speciation, teasing apart the effects of inversions over time remains challenging. For example, are their effects on sequence divergence primarily generated through creating blocks of linkage-disequilibrium pre-speciation or through preventing gene flux after speciation? We provide a comprehensive look into the influence of chromosomal inversions on gene flow throughout the evolutionary history of a classic system: Drosophila pseudoobscura and D. persimilis. We use extensive whole-genome sequence data to report patterns of introgression and divergence with respect to chromosomal arrangements. Overall, we find evidence that inversions have contributed to divergence patterns between Drosophila pseudoobscura and D. persimilis over three distinct timescales: 1) pre-speciation segregation of ancestral polymorphism, 2) post-speciation ancient gene flow, and 3) recent gene flow. We discuss these results in terms of our understanding of evolution in this classic system and provide cautions for interpreting divergence measures in similar datasets in other systems.

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Complex introgression history of the erato-sara clade of Heliconius butterflies

10.1101/2021.02.10.430600 ◽

2021 ◽

Author(s):

Yuttapong Thawornwattana ◽

Fernando A. Seixas ◽

Ziheng Yang ◽

James Mallet

Keyword(s):

Gene Flow ◽

Genomic Sequence ◽

Sequence Data ◽

Whole Genome Sequence ◽

Hybrid Origin ◽

Ancestral Population ◽

Ancestral Gene ◽

Species Phylogeny ◽

Full Likelihood ◽

History Of

AbstractIntrogression plays a key role in adaptive evolution and species diversification in many groups of species including Heliconius butterflies. However, frequent hybridization and subsequent gene flow between species makes estimation of the species phylogeny challenging. Here, we infer species phylogeny and introgression events from whole-genome sequence data of six members of the erato-sara clade of Heliconius using a multispecies coalescent model with introgression (MSci) and an isolation-with-migration (IM) model. These approaches probabilistically capture the genealogical heterogeneity across the genome due to introgression and incomplete lineage sorting in a full likelihood framework. We detect robust signals of introgression across the genome, and estimate the direction, timing and magnitude of each introgression event. The results clarify several processes of speciation and introgression in the erato-sara group. In particular, we confirm ancestral gene flow between the sara clade and an ancestral population of H. telesiphe, a hybrid origin of H. hecalesia, and gene flow between the sister species H. erato and H. himera. The ability to confidently infer the presence, timing and magnitude of introgression events using genomic sequence data is helpful for understanding speciation in the presence of gene flow and will be useful for understanding the adaptive consequences of introgressed regions of the genome. Our analysis serves to highlight the power of full likelihood methods under the MSci model to the history of species divergence and cross-species introgression from genome-scale data.

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Genomic Evidences Support an Independent History of Grapevine Domestication in the Levant

10.1101/2020.07.11.198358 ◽

2020 ◽

Author(s):

Aviad Sivan ◽

Oshrit Rahimi ◽

Mail Salmon-Divon ◽

Ehud Weiss ◽

Elyashiv Drori ◽

...

Keyword(s):

Sequence Data ◽

Genetic Load ◽

Whole Genome Sequence ◽

Local Varieties ◽

Caucasus Region ◽

Demographic Models ◽

Comprehensive Survey ◽

History Of ◽

Distinct Lineage ◽

Pedigree Relationship

AbstractThe ancient grapevines of the Levant have inspired beliefs and rituals in human societies which are still practiced today in religious and traditional ceremonies around the world. Despite their importance, the original Levantine wine-grapes varieties were lost due to cultural turnovers commencing in the 7th century CE, which lead to the collapse of a flourishing winemaking industry in this region. Recently, a comprehensive survey of feral grapevines was conducted in Israel in an attempt to identify local varieties, yet the origin of these domesticated accessions is unclear. Here we study the origin of Levantine grapevines using whole-genome sequence data generated for a diversity panel of wild and cultivated accessions. Comparison between Levantine and Eurasian grapevines indicated that the Levantine varieties represent a distinct lineage from the Eurasian varieties. Demographic models further supported this observation designating that domestication in the Caucasus region predated the emergence of the Levantine samples in circa 5000 years and that authentic descendants of ancient varieties are represented among the Levantine samples. We further explore the pedigree relationship among cultivated grapevines, identify footprints of selective sweeps, and estimate the extent of genetic load in each group. We conclude that the Levantine varieties are distinct from the Eurasian varieties and that resistance to disease and abiotic stress are key traits in the development of both Eurasian and Levantine varieties.

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Whole genome sequence analyses of Western Central African Pygmy hunter-gatherers reveal a complex demographic history and identify candidate genes under positive natural selection

10.1101/022194 ◽

2015 ◽

Author(s):

PingHsun Hsieh ◽

Krishna R Veeramah ◽

Joseph Lachance ◽

Sarah A Tishkoff ◽

Jeffrey D Wall ◽

...

Keyword(s):

Gene Flow ◽

Natural Selection ◽

Muscle Development ◽

Demographic History ◽

Single Pulse ◽

Whole Genome Sequence ◽

Whole Genome ◽

Anatomically Modern Humans ◽

History Of ◽

African Pygmies

African Pygmies practicing a mobile hunter-gatherer lifestyle are phenotypically and genetically diverged from other anatomically modern humans, and they likely experienced strong selective pressures due to their unique lifestyle in the Central African rainforest. To identify genomic targets of adaptation, we sequenced the genomes of four Biaka Pygmies from the Central African Republic and jointly analyzed these data with the genome sequences of three Baka Pygmies from Cameroon and nine Yoruba famers. To account for the complex demographic history of these populations that includes both isolation and gene flow, we fit models using the joint allele frequency spectrum and validated them using independent approaches. Our two best-fit models both suggest ancient divergence between the ancestors of the farmers and Pygmies, 90,000 or 150,000 years ago. We also find that bi-directional asymmetric gene-flow is statistically better supported than a single pulse of unidirectional gene flow from farmers to Pygmies, as previously suggested. We then applied complementary statistics to scan the genome for evidence of selective sweeps and polygenic selection. We found that conventional statistical outlier approaches were biased toward identifying candidates in regions of high mutation or low recombination rate. To avoid this bias, we assigned P-values for candidates using whole-genome simulations incorporating demography and variation in both recombination and mutation rates. We found that genes and gene sets involved in muscle development, bone synthesis, immunity, reproduction, cell signaling and development, and energy metabolism are likely to be targets of positive natural selection in Western African Pygmies or their recent ancestors.

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Phylogenomic Data Reveal Widespread Introgression Across the Range of an Alpine and Arctic Specialist

Systematic Biology ◽

10.1093/sysbio/syaa071 ◽

2020 ◽

Author(s):

Erik R Funk ◽

Garth M Spellman ◽

Kevin Winker ◽

Jack J Withrow ◽

Kristen C Ruegg ◽

...

Keyword(s):

Gene Flow ◽

Genome Sequence ◽

Population Genetic ◽

Approximate Bayesian Computation ◽

Sequence Data ◽

Species Group ◽

Whole Genome Sequence ◽

Whole Genome ◽

Genome Sequence Data ◽

Approximate Bayesian

Abstract Understanding how gene flow affects population divergence and speciation remains challenging. Differentiating one evolutionary process from another can be difficult because multiple processes can produce similar patterns, and more than one process can occur simultaneously. Although simple population models produce predictable results, how these processes balance in taxa with patchy distributions and complicated natural histories is less certain. These types of populations might be highly connected through migration (gene flow), but can experience stronger effects of genetic drift and inbreeding, or localized selection. Although different signals can be difficult to separate, the application of high-throughput sequence data can provide the resolution necessary to distinguish many of these processes. We present whole-genome sequence data for an avian species group with an alpine and arctic tundra distribution to examine the role that different population genetic processes have played in their evolutionary history. Rosy-finches inhabit high elevation mountaintop sky islands and high-latitude island and continental tundra. They exhibit extensive plumage variation coupled with low levels of genetic variation. Additionally, the number of species within the complex is debated, making them excellent for studying the forces involved in the process of diversification, as well as an important species group in which to investigate species boundaries. Total genomic variation suggests a broadly continuous pattern of allele frequency changes across the mainland taxa of this group in North America. However, phylogenomic analyses recover multiple distinct, well supported, groups that coincide with previously described morphological variation and current species-level taxonomy. Tests of introgression using D-statistics and approximate Bayesian computation reveal significant levels of introgression between multiple North American taxa. These results provide insight into the balance between divergent and homogenizing population genetic processes and highlight remaining challenges in interpreting conflict between different types of analytical approaches with whole-genome sequence data. [ABBA-BABA; approximate Bayesian computation; gene flow; phylogenomics; speciation; whole-genome sequencing.]

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Clinal genomic analysis reveals strong reproductive isolation across a steep habitat transition in stickleback fish

Nature Communications ◽

10.1038/s41467-021-25039-y ◽

2021 ◽

Vol 12 (1) ◽

Author(s):

Quiterie Haenel ◽

Krista B. Oke ◽

Telma G. Laurentino ◽

Andrew P. Hendry ◽

Daniel Berner

Keyword(s):

Gene Flow ◽

Reproductive Isolation ◽

Sequence Data ◽

Genomic Analysis ◽

Whole Genome Sequence ◽

Adaptive Divergence ◽

Entire Genome ◽

High Dispersal ◽

A Genome ◽

Habitat Transition

AbstractHow ecological divergence causes strong reproductive isolation between populations in close geographic contact remains poorly understood at the genomic level. We here study this question in a stickleback fish population pair adapted to contiguous, ecologically different lake and stream habitats. Clinal whole-genome sequence data reveal numerous genome regions (nearly) fixed for alternative alleles over a distance of just a few hundred meters. This strong polygenic adaptive divergence must constitute a genome-wide barrier to gene flow because a steep cline in allele frequencies is observed across the entire genome, and because the cline center closely matches the habitat transition. Simulations confirm that such strong divergence can be maintained by polygenic selection despite high dispersal and small per-locus selection coefficients. Finally, comparing samples from near the habitat transition before and after an unusual ecological perturbation demonstrates the fragility of the balance between gene flow and selection. Overall, our study highlights the efficacy of divergent selection in maintaining reproductive isolation without physical isolation, and the analytical power of studying speciation at a fine eco-geographic and genomic scale.

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Distinguishing gene flow between malaria parasite populations

PLoS Genetics ◽

10.1371/journal.pgen.1009335 ◽

2021 ◽

Vol 17 (12) ◽

pp. e1009335

Author(s):

Tyler S. Brown ◽

Olufunmilayo Arogbokun ◽

Caroline O. Buckee ◽

Hsiao-Han Chang

Keyword(s):

Gene Flow ◽

Malaria Parasite ◽

Sequence Data ◽

Spatial Scales ◽

Population Level ◽

Whole Genome Sequence ◽

Surveillance Studies ◽

Migration Rates ◽

Mobility Data ◽

Parasite Populations

Measuring gene flow between malaria parasite populations in different geographic locations can provide strategic information for malaria control interventions. Multiple important questions pertaining to the design of such studies remain unanswered, limiting efforts to operationalize genomic surveillance tools for routine public health use. This report examines the use of population-level summaries of genetic divergence (FST) and relatedness (identity-by-descent) to distinguish levels of gene flow between malaria populations, focused on field-relevant questions about data size, sampling, and interpretability of observations from genomic surveillance studies. To do this, we use P. falciparum whole genome sequence data and simulated sequence data approximating malaria populations evolving under different current and historical epidemiological conditions. We employ mobile-phone associated mobility data to estimate parasite migration rates over different spatial scales and use this to inform our analysis. This analysis underscores the complementary nature of divergence- and relatedness-based metrics for distinguishing gene flow over different temporal and spatial scales and characterizes the data requirements for using these metrics in different contexts. Our results have implications for the design and implementation of malaria genomic surveillance studies.

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Phylogeographic Inference Using Approximate Likelihoods

10.1101/025353 ◽

2015 ◽

Cited By ~ 3

Author(s):

Brian C O'Meara ◽

Nathan D Jackson ◽

Ariadna E Morales-Garcia ◽

Bryan C Carstens

Keyword(s):

Gene Flow ◽

Demographic History ◽

A Priori ◽

Evolutionary Process ◽

Population Divergence ◽

Parameter Estimates ◽

Single Model ◽

History Of ◽

Tree Methods

The demographic history of most species is complex, with multiple evolutionary processes combining to shape the observed patterns of genetic diversity. To infer this history, the discipline of phylogeography has (to date) used models that simplify the historical demography of the focal organism, for example by assuming or ignoring ongoing gene flow between populations or by requiring a priori specification of divergence history. Since no single model incorporates every possible evolutionary process, researchers rely on intuition to choose the models that they use to analyze their data. Here, we develop an approach to circumvent this reliance on intuition. PHRAPL allows users to calculate the probability of a large number of demographic histories given their data, enabling them to identify the optimal model and produce accurate parameter estimates for a given system. Using PHRAPL, we reanalyze data from 19 recent phylogeographic investigations. Results indicate that the optimal models for most datasets parameterize both gene flow and population divergence, and suggest that species tree methods (which do not consider gene flow) are overly simplistic for most phylogeographic systems. These results highlight the importance of phylogeographic model selection, and reinforce the role of phylogeography as a bridge between population genetics and phylogenetics.

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Distinguishing gene flow between malaria parasite populations

10.1101/2021.01.08.425858 ◽

2021 ◽

Author(s):

Tyler Steven Brown ◽

Aimee R. Taylor ◽

Olufunmilayo Arogbokun ◽

Caroline O. Buckee ◽

Hsiao-Han Chang

Keyword(s):

Gene Flow ◽

Malaria Parasite ◽

Sequence Data ◽

Simulated Data ◽

Whole Genome Sequence ◽

Effective Population ◽

Migration Rates ◽

Population Sizes ◽

And Migration ◽

Parasite Populations

Measuring gene flow between malaria parasite populations in different geographic locations can provide strategic information for malaria control interventions. Multiple important questions pertaining to the design of such studies remain unanswered, limiting efforts to operationalize genomic surveillance tools for routine public health use. This report evaluates numerically the ability to distinguish different levels of gene flow between malaria populations, using different amounts of real and simulated data, where data are simulated using parameters that approximate different epidemiological conditions. Specifically, using Plasmodium falciparum whole genome sequence data and sequence data simulated for a metapopulation with different migration rates and effective population sizes, we compare two estimators of gene flow, explore the number of genetic markers and number of individuals required to reliably rank highly connected locations, and describe how these thresholds change given different effective population sizes and migration rates. Our results have implications for the design and implementation of malaria genomic surveillance efforts.

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